Predicting undernutrition among elementary schoolchildren in the Philippines using machine learning algorithms

Predicting undernutrition among elementary schoolchildren in the Philippines using machine learning algorithms

Objectives This study aimed to compare the accuracy of four machine-learning (ML) algorithms, using two classification schemes, to predict undernutrition based on individual and household risk factors. Methods Data on public-school children were collected from a rural province (310 children) and a...

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Bibliographic Details
Main Authors: Siy Van, Vanessa T, Antonio, Victor A, Siguin, Carmina P, Gordoncillo, Normahitta P., Sescon, Joselito T., Go, Clark C, Miro, Eden Delight
Format: text
Published: Archīum Ateneo 2022
Subjects:
Nutrition
Machine learning
Philippines
Random forest
Prediction
Energy
Classification
Mathematics
Medicine and Health Sciences
Online Access:https://archium.ateneo.edu/mathematics-faculty-pubs/213
https://doi.org/10.1016/j.nut.2021.111571
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Institution: Ateneo De Manila University

Internet

https://archium.ateneo.edu/mathematics-faculty-pubs/213
https://doi.org/10.1016/j.nut.2021.111571

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